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Rohan Paul· @rohanpaul_ai · X· · 原发布时间 AI 评分54

Nace AI 发布 27B 决策模型 Drex Max,按选项返回概率

AI 导读

Drex Max 读取上下文和问题后,在一次前向计算中为给定选项分别返回概率,不生成回答文本。发布者称,其在 Decision Bench v4 上与 GPT-6 Sol 的成绩在统计上持平,每千次决策成本为 0.06 美元、耗时 183 毫秒;在不使用思维链或工具的抽样 HLE 题目中,答对率为 21%。

原帖引用 · 原文

@rohanpaul_ai

This is a brilliant release from @NaceAI .

It goes after the costly part of AI agents, the thousands of small choices, with a 27B model that only picks and never writes.

- Nace AI’s 27B Drex Max statistically ties GPT-6 Sol on Decision Bench v4 without generating a token.

- It reads a context and question, then returns one probability per supplied option in a single forward pass.

- Its RLAF training rewards verified answers plus a reasoning judge’s probabilities, while a KL penalty limits drift from supervised training.

- Drex Max costs $0.06 per 1K decisions at 183 ms, against $10.17 and about 3.5 seconds for Claude Opus 5.5.

Without chain-of-thought or tools, it answers 21% of sampled HLE questions against 56% for Opus.

引用Nace AI@NaceAI
How are Decision Models Trained? Today, we are publishing the Drex Technical Report for the developer community! 🚀 Discover details on how the State-of-the-art Open-Source decision models are trained with RLAF. Build more at: https://t.co/swZ0gsqCyo (try for free) P.S. Drex Max 1.1 and Drex for Finance are closed sourced and designed for enterprise use-cases
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来源:Rohan Paul · x.com

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